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Consists of editing, coding, data entry, and data cleaning.
Graphic depiction of a bivariate distribution.
Detecting and resolving errors in coding and data entry.
Replacing missing values in data analysis by estimating values from the available data.
Shows whether the association in a contingency table is statistically significant.
The middle value in a distribution.
Documentation for a data file that usually contains the question wording and responses codes for each variable.
Examples are Cramer’s phi and the correlation coefficient.
The value or category in a distribution with the highest frequency.
A graphic display of a univariate distribution.
The most commonly used statistical measure of variation.
A cleaning technique that can be programmed for automatic detection in computer-assisted interviewing.